Over the last several decades, biotechnology has become increasingly fundamental to our society and now has a major impact on the production of food, medicine, fuel, and materials. This importance and influence on our day to day lives has led to a desire to better monitor and control the processes used to implement this technology. In part due to these reasons, and to end a stagnant period in the technological advancement of drug development, the US FDA has created the PAT (Process Analytical Technology) initiative. This initiative encourages not only large pharmaceutical manufacturers but also smaller modem biotech companies to bring new technological advances into mainstream use to help modernize and optimize biotech manufacturing. Much of the impetus for the PAT initiative is to bring about advances in monitoring and control so that drug manufacturing is safer, more repeatable, more transparent, and less expensive and thereby protect the public. For example, in the “Process Control Tools” section of the PAT guidance document, it states that:                “Strategies should accommodate the attributes of the input materials, the ability and reliability of the process analyzers to measure critical analytes, and the achievement of process endpoints to ensure consistent quality of the output materials and final product.” Design optimization of drug formulation and manufacturing and processes within the PAT framework can include the following steps:        Identify and measure critical material and bio-process attributes relating to product quality        Development of a process measurement system that allows real-time or near real-time (e.g. on-line or at-line) monitoring of critical bio-process/product attributes        Design process controls that enable adjustment to ensure that critical process parameters are controlled        Develop mathematical relationships between product quality attributes and measurements of critical material and process attributes        
Much of this can be summarized to mean that by using advanced monitoring of materials used and process variables (e.g.: pH, dissolved oxygen, dissolved CO2, glucose, glutamine, lactate, ammonia) mathematical models of a bio-process can be created. Through the use of these models, the process yield can be predicted and thereby lead to optimized growth runs even if every process parameter is not fully understood. Once monitoring systems are in-place and models created, advanced control systems can be used to implement the optimization procedures.
In the future, for a typical microbial or cell growth run to conform to the PAT initiative as outlined above, it is likely that all the raw materials and also the data used in the growth process will need be recorded and tracked. For instance, the growth media manufacturer's formulation specifics, lot data and manufacture date will need to be logged so that issues like contamination, expiration, or other factors affecting quality or performance can be tracked. The same will be true for the actual cell line used, the pH buffer employed, the glucose feed, the sensor manufacturing data, and other inputs. As the trend towards disposable bioreactors, disposable sensors, and other disposable materials mature and become a major part of the manufacturing chain these items will need to be tracked as well.